The Siemens Community Catalyst program was co-created with our community to acknowledge technology leaders who consistently contribute to the Siemens Community. Nominations are accepted on a rolling basis.
k-Means and k-Medoids both take an initial random sample from the data as starting centroids for the clustering. This random selection is guided by a random number generator and this number generator again delivers a sequence of random numbers depending on the random seed. On the one hand, this ensures that you will get a sequence of random numbers, on the other hand for the same random seed number, you will always get exactly the same random numbers. Hence, your experiments can be reproduced as long as the same random number seeds are used.
Join us for a community conversation on how High-Performance Computing (HPC) and Simcenter PSIM work together to meet the increasing demands of modern power electronics simulation. During this one-hour technical session, you'll discover how leveraging HPC can speed up simulations, improve scalability, and empower engineers…
Join us for a community conversation on accelerating your motor simulation workflow with Simcenter Simlab. In this beginner-friendly session, we'll introduce the platform's automated model-building capabilities and show how easy it is to set up your first electric motor analysis. You'll see the basic steps of geometry…
Join us for a Community Conversation where we'll discuss practical approaches to analyzing complex electromagnetic models using hybrid solver techniques. This session will provide a general overview of how different computational methods can be combined within a single simulation to address models containing varied…
